政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/59281
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113656/144643 (79%)
Visitors : 51724933      Online Users : 428
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/59281


    Title: 空間自相關模型下空間群聚檢定
    Spatial Clusters in a Global-dependence Model
    Authors: 王泰期
    Wang, Tai Chi
    Contributors: 余清祥
    王泰期
    Wang, Tai Chi
    Keywords: 群聚偵測
    空間自相關
    空間掃描統計量
    空間自相關模型
    EM演算法
    Date: 2012
    Issue Date: 2013-09-02 15:35:34 (UTC+8)
    Abstract: 因為疾病空間模式通常會與環境中的危險因子有很強烈的關聯性，因此流行病學家與社會大眾都對疾病的空間模式感到興趣。舉例來說，空間群聚就是一項非常受到重視的疾病空間模式，在眾多的空間群聚檢定方法種，Kulldorff和 Nagarwalla在1995年提出的空間掃描統計量是相當受到廣泛應用的方法，雖然這個統計方法可以檢定初空間資料的異質性，但是卻沒有辦法區隔這些異質性是來自於整體空間資料的相關性或是局部的空間群聚。在本篇論文中，我們將分別提出計次型的統計方法與貝氏統計方法兩種類型的空間群聚檢定方法來處理這樣的問題，其中計次型的統計方法為一兩階段的統計方法，首先採用EM演算法來估計空間自相關，並根據估計的結果與掃描窗格在偵測空間群聚；另一方面，貝氏方法則考慮加入群聚的中心位置及半徑作為事前的機率分布，進而透過MCMC的方法來計算出後驗分布的結果。除此之外，北卡羅來納的嬰兒猝死症和台灣老年人口癌症死亡資料將被用來示範與評價不同群聚檢定方法的差異與效果。
    Reference: Anselin, L. (1995). Local indicators of spatial associationlisa. Geographical analysis, 27 (2), 93–115.
    Banerjee, S., Carlin, B., & Gelfand, A. (2004). Hierarchical Modeling and Analysis for Spatial Data. Chapman & Hall: London.
    Besag, J. (1974). Spatial interaction and the statistical analysis of lattice systems. Journal of the Royal Statistical Society. Series B (Methodological), 36 (2), 192–236.
    Besag, J. (1975). Statistical analysis of non-lattice data. The statistician, 179–195.
    Besag, J. (1977). Efficiency of pseudo-likelihood estimation for simple gaussian fields. Biometrika, 64 , 616–618.
    Besag, J. & Newell, J. (1991). The detection of clusters in rare diseases. Journal of the Royal Statistical Society. Series A (Statistics in Society), 143–155.
    Besag, J., York, J., & Molli´e, A. (1991). Bayesian image restoration, withtwo applications in spatial statistics. Annals of the Institute of Statistical Mathematics, 43 (1), 1–59.
    Best, N., Richardson, S., & Thomson, A. (2005). A comparison of bayesian spatial models for disease mapping. Statistical Methods in Medical Research, 14 (1), 35–59.
    Clayton, D. & Bernardinelli, L. (1992). Bayesian methods for mapping disease risk. In P. Elliott, J. Cuzick, D. English, and R. Stern (Eds.), Geographical and Environmental Epidemiology: Methods for Small-Area Studies. Oxford: Oxford University Press.
    Cressie, N. (1993). Statistics for Spatial Data, revised edition. Wiley: New York.
    Cressie, N. & Chan, N. (1989). Spatial modeling of regional variables. Journal of the American Statistical Association, 84 (406), 393–401.
    Gangnon, R. & Clayton, M. (2000). Bayesian detection and modeling of spatial disease clustering. Biometrics, 56 (3), 922–935.
    Geary, R. (1954). The contiguity ratio and statistical mapping. The incorporated statistician, 5 (3), 115–146.
    Getis, A. & Ord, J. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24 (3), 189–206.
    Hammersley, J. M. & Clifford, P. (1971). Markov fields on finite graphs and lattices. 1971. Unpublished manuscript, cited in [Ish81].
    Hastings, W. K. (1970). Monte carlo sampling methods using markov chains and their applications. Biometrika, 57 (1), 97–109.
    Huang, L., Kulldorff, M., & Gregorio, D. (2007). A spatial scan statistic for survival data. Biometrics, 63 (1), 109–118.
    Huang, L., Pickle, L. W., & Das, B. (2008). Evaluating spatial methods for investigating global clustering and cluster detection of cancer cases. Statistics in Medicine, 27 (25), 5111–5142.
    Jung, I. (2009). A generalized linear models approach to spatial scan statistics for covariate adjustment. Statistics in Medicine, 28 (7), 1131–1143.
    Jung, I., Kulldorff, M., & Klassen, A. (2007). A spatial scan statistic for ordinal data. Statistics in Medicine, 26 (7), 1594–1607.
    Knox, E. & Bartlett, M. (1964). The detection of space-time interactions. Journal of the Royal Statistical Society. Series C (Applied Statistics), 13 (1), 25–30.
    Kulldorff, M. (1997). A spatial scan statistic. Communications in Statistics-Theory and Methods, 26 (6), 1481–1496.
    Kulldorff, M. (2001). Prospective time periodic geographical disease surveillance using a scan statistic. Journal of the Royal Statistical Society: Series A (Statistics in Society), 164 (1), 61–72.
    Kulldorff, M. (2006). Tests of spatial randomness adjusted for an inhomogeneity: a general framework. Journal of the American Statistical Association, 101 (475), 1289–1305.
    Moran, P. (1950). Notes on continuous stochastic phenomena. Biometrika, 17–23.
    Openshaw, S., Charlton, M., Craft, A., & Birch, J. (1988). Investigation of leukaemia clusters by use of a geographical analysis machine. The Lancet , 331 (8580), 272–273.
    Ord, J. K. & Getis, A. (1995). Local spatial autocorrelation statistics: distributional issues and an application. Geographical Analysis, 27 (4), 286–306.
    Ord, J. K. & Getis, A. (2001). Testing for local spatial autocorrelation in the presence of global autocorrelation. Journal of Regional Science, 41 (3), 411–432.
    Patil, G. & Taillie, C. (2004). Upper level set scan statistic for detecting arbitrarily shaped hotspots. Environmental and Ecological Statistics, 11 (2), 183–197.
    Rencher, A. (2000). Linear Models in Statistics. Wiley: New York.
    Richardson, S., Thomson, A., Best, N., & Elliott, P. (2004). Interpreting posterior relative risk estimates in disease-mapping studies. Environmental Health Perspectives, 112 (9), 1016–1025.
    Spiegelhalter, D., Thomas, A., Best, N., & Lunn, D. (2003). Winbugs user manual. Cambridge: MRC Biostatistics Unit .
    Tango, T. & Takahashi, K. (2005). A flexibly shaped spatial scan statistic for detecting clusters. International Journal of Health Geographics, 4 (1), 11.
    Thomas, A., Best, N., Lunn, D., Arnold, R., & Spiegelhalter, D. (2004). Geobugs user manual. Cambridge: MRC Biostatistics Unit .
    Tiefelsdorf, M., Griffith, D., & Boots, B. (1999). A variance-stabilizing coding scheme for spatial link matrices. Environment and Planning A, 31 (1), 165–180.
    Turnbull, B., Iwano, E., Burnett, W., Howe, H., & Clark, L. (1990). Monitoring for clusters of disease: application to leukemia incidence in upstate new york. American Journal of Epidemiology, 132 (supp1), 136–143.
    Wang, T.-C. & Yue, C.-S. J. (2013a). A binary-based approach for detecting irregularly shaped clusters. International journal of health geographics, 12 (1), 25.
    Wang, T.-C. & Yue, C.-S. J. (2013b). Spatial clusters in a global-dependence model. Spatial and Spatio-temporal Epidemiology, 5 , 39–50.
    Zeger, S. L., Liang, K.-Y., & Albert, P. S. (1988). Models for longitudinal data: a generalized estimating equation approach. Biometrics, 1049–1060.
    Description: 博士
    國立政治大學
    統計研究所
    95354504
    101
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0095354504
    Data Type: thesis
    DOI link: http://dx.doi.org/10.1016/j.sste.2013.03.003
    DOI: 10.1016/j.sste.2013.03.003
    Appears in Collections:[Department of Statistics] Theses

    Files in This Item:

    File SizeFormat
    450401.pdf10047KbAdobe PDF2528View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback